Intelligent search results blending

Abstract

The subject invention relates to systems and methods that automatically combine or interleave received search results from across knowledge databases in a uniform and consistent manner. In one aspect, an automated search results blending system is provided. The system includes a search component that directs a query to at least two databases. A learning component is employed to rank or score search results that are received from the databases in response to the query. A blending component automatically interleaves or combines the results according to the rank in order to provide a consistent ranking system across differing knowledge sources and search tools.

Description

TECHNICAL FIELD [0001] The subject invention relates generally to computer systems, and more particularly, relates to systems and methods that employ machine learning techniques to rank and order search results from multiple search sources in order to provide a blended return of the results in terms of relevance to a search query. BACKGROUND OF THE INVENTION [0002] Given the popularity of the World Wide Web and the Internet, users can acquire information relating to almost any topic from a large quantity of information sources. In order to find information, users generally apply various search engines to the task of information retrieval. Search engines allow users to find Web pages containing information or other material on the Internet or internal databases that contain specific words or phrases. For instance, if they want to find information about a breed of horses known as Mustangs, they can type in “Mustang horses”, click on a search button, and the search engine will return a...

AI Technical Summary

Benefits of technology

[0006] The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This summary is not an extensive overview of the invention. It is not intended to identify key/critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present some concepts of the invention in a simplified form as a prelude to the more detailed description that is presented later.

[0007] The subject invention relates to systems and methods that utilize machine learning techniques to analyze query results from multiple search sources in order to blend results across the sources in terms of relevance. In one aspect, one or more learning components (e.g., classifiers) are adapted to search engine databases to determine relevance of information residing on a respective database. The learning components can be trained from a plurality of factors such as query term frequency appearing in a database, how recent a term has been used, time considerations, the number of times a given term has been searched for on a given database, the number of document examinations requested from the database, other metadata considerations and

Problems solved by technology

Thus, manual narrowing of terms saves users a lot of time by helping to mitigate receiving several thousand sites to sort through when looking for specific information.

Unfortunately, there is no standard for ranking documents from different search engines, whereby different search engine algorithms rank results inconsistently from one another.

One problem with current searching techniques relates to how to compare, rank, and / or display information that may have been retrieved from multiple database sources.

Consequently, it is difficult for users to determine the importance or relevance of returned information given the somewhat incompatible ranking standards that are employed by different search tools.

Also, this type of searching and analysis can take particularly large amounts of time to sift through results from each site and also to manually prioritize the information received given that some sites or engines likely may rank returned documents or information sources differently.

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